Persaingan PayLater di Indonesia: Analisis Pasar dan Peramalan Minat Konsumen Berbasis Data Science

Abstract

This study examines the dynamics of consumer interest in PayLater services in Indonesia by leveraging big data from Google Trends for the 2023–2025 period. Using a qualitative approach that integrates spatial analysis and Python-based predictive modeling, this research aims to map temporal search patterns, the geographical distribution of adoption, and the socio-economic factors influencing consumer preference toward three major platforms: Kredivo, Akulaku, and Shopee PayLater. The methodology includes time-series analysis, provincial-level geospatial mapping, and forecasting using the Facebook Prophet algorithm. The findings reveal that PayLater search interest is cyclical, with significant spikes during e-commerce campaigns, public holidays, and monthly payday cycles. Spatially, a sharp adoption disparity exists between urban areas and regions with limited digital infrastructure. Kredivo exhibits the most balanced regional distribution, while Akulaku is heavily concentrated in West Java, and Shopee PayLater shows strong penetration in non-Java regions. The forecasting results project sustained growth in interest through 2027, providing strategic implications for fintech companies in expanding digital financial inclusion across Indonesia.